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Title: Optimizing the performance of reactive molecular dynamics simulations for many-core architectures

Abstract

Reactive molecular dynamics simulations are computationally demanding. Reaching spatial and temporal scales where interesting scientific phenomena can be observed requires efficient and scalable implementations on modern hardware. In this article, we focus on optimizing the performance of the widely used LAMMPS/ReaxC package for many-core architectures. As hybrid parallelism allows better leverage of the increasing on-node parallelism, we adopt thread parallelism in the construction of bonded and nonbonded lists and in the computation of complex ReaxFF interactions. To mitigate the I/O overheads due to large volumes of trajectory data produced and to save users the burden of post-processing, we also develop a novel in situ tool for molecular species analysis. We analyze the performance of the resulting ReaxC-OMP package on two different architectures: (i) Mira, an IBM Blue Gene/Q system and (ii) Cori-II, a Cray XC-40 sytem with Knights Landing processors. For Pentaerythritol tetranitrate (PETN) systems of sizes ranging from 32 thousand to 16.6 million particles, we observe speedups in the range of 1.5-4.5x. We observe sustained performance improvements for up to 262,144 cores (1,048,576 processes) of Mira and a weak scaling efficiency of 91.5% in large simulations containing 16.6 million particles. Finally, the in situ molecular species analysis tool incursmore » only insignificant overheads across various system sizes and runs configurations.« less

Authors:
 [1];  [2];  [2];  [3];  [4];  [2]
+ Show Author Affiliations
  1. Michigan State Univ., East Lansing, MI (United States). Dept. of Computer Science and Engineering; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Computational Research Division
  2. Argonne National Lab. (ANL), Argonne, IL (United States). Argonne Leadership Computing Facility
  3. Michigan State Univ., East Lansing, MI (United States). Dept. of Computer Science and Engineering
  4. Sandia National Lab. (SNL-CA), Livermore, CA (United States). Multiscale Science Dept.
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
Argonne National Laboratory (ANL), Argonne, IL (United States). Argonne Leadership Computing Facility
OSTI Identifier:
1530430
Grant/Contract Number:  
AC02-06CH11357
Resource Type:
Accepted Manuscript
Journal Name:
International Journal of High Performance Computing Applications
Additional Journal Information:
Journal Volume: 33; Journal Issue: 2; Journal ID: ISSN 1094-3420
Publisher:
SAGE
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; hybrid MPI/OpenMP parallelism; LAMMPS-ReaxC-OMP; multi-core architectures; reactive molecular dynamics; ReaxFF; many-core architectures

Citation Formats

Aktulga, Hasan Metin, Knight, Chris, Coffman, Paul, O’Hearn, Kurt A., Shan, Tzu-Ray, and Jiang, Wei. Optimizing the performance of reactive molecular dynamics simulations for many-core architectures. United States: N. p., 2018. Web. doi:10.1177/1094342017746221.
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Aktulga, Hasan Metin, Knight, Chris, Coffman, Paul, O’Hearn, Kurt A., Shan, Tzu-Ray, & Jiang, Wei. Optimizing the performance of reactive molecular dynamics simulations for many-core architectures. United States. https://doi.org/10.1177/1094342017746221
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Aktulga, Hasan Metin, Knight, Chris, Coffman, Paul, O’Hearn, Kurt A., Shan, Tzu-Ray, and Jiang, Wei. Mon . "Optimizing the performance of reactive molecular dynamics simulations for many-core architectures". United States. https://doi.org/10.1177/1094342017746221. https://www.osti.gov/servlets/purl/1530430.
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@article{osti_1530430,
title = {Optimizing the performance of reactive molecular dynamics simulations for many-core architectures},
author = {Aktulga, Hasan Metin and Knight, Chris and Coffman, Paul and O’Hearn, Kurt A. and Shan, Tzu-Ray and Jiang, Wei},
abstractNote = {Reactive molecular dynamics simulations are computationally demanding. Reaching spatial and temporal scales where interesting scientific phenomena can be observed requires efficient and scalable implementations on modern hardware. In this article, we focus on optimizing the performance of the widely used LAMMPS/ReaxC package for many-core architectures. As hybrid parallelism allows better leverage of the increasing on-node parallelism, we adopt thread parallelism in the construction of bonded and nonbonded lists and in the computation of complex ReaxFF interactions. To mitigate the I/O overheads due to large volumes of trajectory data produced and to save users the burden of post-processing, we also develop a novel in situ tool for molecular species analysis. We analyze the performance of the resulting ReaxC-OMP package on two different architectures: (i) Mira, an IBM Blue Gene/Q system and (ii) Cori-II, a Cray XC-40 sytem with Knights Landing processors. For Pentaerythritol tetranitrate (PETN) systems of sizes ranging from 32 thousand to 16.6 million particles, we observe speedups in the range of 1.5-4.5x. We observe sustained performance improvements for up to 262,144 cores (1,048,576 processes) of Mira and a weak scaling efficiency of 91.5% in large simulations containing 16.6 million particles. Finally, the in situ molecular species analysis tool incurs only insignificant overheads across various system sizes and runs configurations.},
doi = {10.1177/1094342017746221},
journal = {International Journal of High Performance Computing Applications},
number = 2,
volume = 33,
place = {United States},
year = {Mon Jan 08 00:00:00 EST 2018},
month = {Mon Jan 08 00:00:00 EST 2018}
}
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https://doi.org/10.1177/1094342017746221
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